CN117425583A

CN117425583A - Vehicle control unit for vehicle power management

Info

Publication number: CN117425583A
Application number: CN202180098977.XA
Authority: CN
Inventors: 阿米尔·阿默尔
Original assignee: Huawei Technologies Co Ltd
Current assignee: Huawei Technologies Co Ltd
Priority date: 2021-10-19
Filing date: 2021-10-19
Publication date: 2024-01-19
Also published as: EP4405203A1; WO2023066467A1

Abstract

A vehicle control unit (vehicle control unit, VCU) (110) for vehicle power management receives battery temperature data. The battery temperature data is indicative of a battery temperature (111) of a battery (120) of the vehicle. Based on a comparison of the battery temperature (111) and a temperature threshold, the VCU determines a power allocation (133), the power allocation (133) being used to allocate charging power (134) provided by a charging system (130). The power distribution (133) indicates a division of the charging power (134) into a first portion (131) for charging the battery (120) by the charging system (130) and a second portion (132) for heating the battery (120) by a heating system (140). The VCU transmits information (112) about the first portion (131) of the charging power (134) to the charging system (130) and transmits information (113) about the second portion (132) of the charging power (134) to the heating system (140).

Description

Vehicle control unit for vehicle power management

Technical Field

The invention relates to a vehicle control unit for vehicle power management and a corresponding method, a vehicle charging control system and a network device of a cloud network. The invention relates in particular to the field of low-temperature charging of electric vehicles and HV (high voltage) batteries. In particular, the present invention relates to low temperature charging of a time-optimized HV battery using an external charger and an external heater.

Background

HV battery low temperature charging is a problem faced by original equipment manufacturers (original equipment manufacturer, OEM) and Electric Vehicle (EV) users due to power limitations imposed by cell chemistry. The resistance of the battery cell at low temperatures is higher, which limits the amount of charging current that can be supplied to the battery. Another problem is lithium plating, which may be exacerbated by high charging currents at low temperatures. Cell manufacturers typically provide information about power derating, which may be expressed as a charge/discharge power or current limit curve versus cell temperature. At the system level, a battery management system (battery management system, BMS) provider can integrate this information and provide a battery level power derating curve.

EV users living in cold regions face the problem of limited charging, usually due to BMS power limitations, if they wish to charge their cars at night using a household charger or electric vehicle power supply equipment (Electric Vehicle Supply Equipment, EVSE). The next day the user finds that the State-of-Charge (SoC) level of the vehicle battery is low.

Disclosure of Invention

The object of the present invention is to provide a solution for efficiently charging a battery of an electric vehicle at low temperature.

It is an object of the present invention, inter alia, to provide a concept for low temperature charging of HV batteries using a heating system and an on-board charger connected to the EVSE.

This object is achieved by the features of the independent claims. Other embodiments are evident from the dependent claims, the description and the drawings.

EVs are equipped with heating systems that can use electrical energy to provide heat to vehicle components, including batteries. By increasing the battery temperature, the power limit increases, and more charge current may be provided to the battery cells.

The present invention describes a mechanism to optimally utilize the heating process prior to the charging process in order to achieve maximum energy transfer to the battery and thus achieve as high a SoC as possible.

The solution proposed in the present invention corresponds to a solution to the optimal control problem. The objective of the solution to the optimal control problem is to: an optimal power allocation lambda of the charging power provided by the OBC is found between the power provided to the battery for charging and the power consumed by the thermal system to provide heat to the battery.

The scheme is based on a mathematical model of the presence of a priori knowledge or empirical data or the following information: a battery self-heating model that depends on different charging currents and/or powers; a battery temperature profile based on heat transferred to the battery; a plot of battery OCV versus SOC (open circuit voltage versus state of charge); the power consumption of a thermal system is related to the amount of heat generated by the thermal system.

For purposes of describing the present invention in detail, the following terms, abbreviations and symbols are used:

OEM original Equipment manufacturer

EV electric vehicle

VCU vehicle control unit

BMS battery management system

HV high voltage

LV low pressure

SoC state of charge

SoH health status

OCV open circuit voltage

OBC vehicle-mounted charger

DC direct current

AC power

EVSE electric vehicle power supply equipment

In the present invention, an electric vehicle, a vehicle control unit, and a battery management system are described. An Electric Vehicle (EV) is a vehicle propelled using one or more electric motors. The electric vehicle may be autonomously powered by the battery. EVs include, but are not limited to, road and rail vehicles, surface and underwater boats, electric airplanes, and electric spacecraft.

The vehicle control unit or VCU is a supervisory controller for an electric vehicle or a hybrid vehicle. The vehicle control unit functions as a domain controller of an electric vehicle or a hybrid vehicle. The VCU reads sensor signals, such as brake, high-voltage interlock loop (HVIL), or charger connection. The VCU then acts to balance system energy, optimize torque, control the motor, HV battery, and on-board charging system until the charger is locked.

A battery management system (battery management system, BMS) is any electronic system that manages rechargeable batteries (cells or battery packs), for example by protecting the batteries from operating outside their safe operating area, monitoring battery status, calculating secondary data, reporting this data, controlling battery environment, validating and/or balancing the batteries.

According to a first aspect, the invention relates to a vehicle control unit for vehicle power management. Wherein the vehicle control unit is configured to: receiving battery temperature data, the battery temperature data being indicative of a battery temperature of a battery of the vehicle; determining a power distribution for distributing charging power provided by a charging system based on a comparison of the battery temperature and a temperature threshold, wherein the power distribution indicates dividing the charging power into a first portion for charging the battery by the charging system and a second portion for heating the battery by a heating system; information about the first portion of the charging power is sent to the charging system and information about the second portion of the charging power is sent to the heating system.

The vehicle control unit provides an efficient solution for charging the battery of an electric vehicle at low temperatures. The VCU may detect a globally optimal power allocation according to an optimal control solution. The VCU allows application-independent charging according to an optimal charging strategy independent of the OBC maximum power, battery chemistry or thermal system type. VCU can be advantageously extended to multi-objective optimization, e.g., optimizing the final temperature by SoC boundary conditions; the cost function is optimized by different weighting factors of the final SoC and the final temperature.

Battery temperature data including battery temperature may be received from a battery management system (Battery Management System, BMS). The battery management system is connected to all of the battery cells of the battery pack and receives voltage and temperature information monitored by the sensors from each module. The BMS also has a current sensor for monitoring the current in the battery pack. The BMS transmits minimum and maximum temperatures of the battery cells, soC, soH, etc., to the VCU.

The temperature threshold means that full-power charging cannot be performed below this temperature. For example 10 ℃, but the temperature threshold is highly dependent on the cell manufacturer and the cell topology inside the battery (e.g., how many cells are connected in series or parallel).

In an exemplary embodiment of the vehicle control unit, the power distribution comprises a power distribution factor indicating a first portion of the charging power for charging the battery and a second portion of the charging power for heating the battery.

This provides the advantage that the power division factor can easily be used to calculate the first and second part of the charging power.

In an exemplary embodiment of the vehicle control unit, the power distribution is based on a charging strategy indicating the power distribution as a function of the state of charge of the battery and the battery temperature during a charging time.

This provides the advantage that the charging strategy can be determined offline, and a scheme of optimal charging strategies for different initial conditions can be efficiently requested, e.g. from a cloud storing optimal charging strategies.

The optimal charging strategy refers to following the power allocation obtained from solving the optimization problem.

In an exemplary embodiment of the vehicle control unit, the power distribution is based on at least one of a thermal model of the battery, a derating model of the battery, a power consumption model of the heating system, a relationship between heat generated by the heating system and corresponding power consumption, and an electrical model of the battery.

This provides the advantage that including various information can be used to determine the optimal power allocation. From all this information, a globally optimal power allocation can be determined.

In an exemplary embodiment of the vehicle control unit, the charging strategy is used to obtain a maximum state of charge of the battery during a charging time interval.

This provides the advantage that the maximum state of charge can be flexibly determined from the expected charging time interval, for example from the expected departure time.

The maximum state of charge at the end of the charging session may be obtained by defining a cost function for the optimizer. An exemplary cost function may be, for example, 100% -SoC (tf). SoC (tf) is the SoC at the end of the optimization period, and corresponds to the SoC at the end of the charging session. The task of the optimizer is to minimize this function while finding the optimal power allocation λ. After solving this problem, the power allocation that maximizes the SoC at tf can be determined.

In an exemplary embodiment of the vehicle control unit, the vehicle control unit is adapted to receive the power allocation from a memory segment storing one or more predefined values, wherein the memory segment is adapted to store the power allocation for consecutive charging times.

This provides the advantage that the power allocation according to the optimal solution can be determined offline and stored in a memory segment, e.g. in a look-up table, for access.

In an exemplary embodiment of the vehicle control unit, the vehicle control unit is configured to download the memory segment from a network device of a cloud network.

This provides the advantage that the VCU may not have to deal with optimization problems. Thus, the computational complexity of the VCU in terms of processing power can be reduced.

In an exemplary embodiment of the vehicle control unit, the vehicle control unit is adapted to: transmitting a current vehicle state to the network device of the cloud network; the memory segment of the current vehicle state is received from the network device of the cloud network. Wherein the current vehicle state includes at least one of: the battery temperature, the state of charge of the battery, the maximum power provided by the charging system, and the departure time.

This provides the advantage that the network device can calculate or determine an optimal solution for the power distribution according to the specific requirements of the vehicle given by the vehicle state. Thus, the VCU may save processing power.

In an exemplary embodiment of the vehicle control unit, the power distribution is based on: a derating function of the battery based on the battery temperature.

This provides the advantage that the optimal power allocation can be accurately determined when using the derating function of the battery. The derating function is a function that gives a relationship between the battery temperature and the maximum charge power or current that the battery can receive. This relationship may depend on the cell chemistry and safety margin chosen by the system designer.

In an exemplary embodiment of the vehicle control unit, the power distribution is based on: the voltage of the battery based on the state of charge of the battery.

This provides the advantage that the optimal power allocation can be accurately determined by taking into account the voltage of the battery, which may vary with the state of charge of the battery.

The nominal voltage of the battery depends on the state of charge of the battery, and also on the current due to the internal resistance and capacitance of the battery. When the battery is fully charged, the voltage provided by the battery may be higher than an empty battery. There is a relationship between the state of charge of the battery and the voltage provided by the battery, which can be described by a specific function. By taking these relationships into account, the optimal power allocation can be efficiently determined.

In an exemplary embodiment of the vehicle control unit, the power distribution is based on at least one of the following information: a battery self-heating model indicating the battery temperature from a charge current or power, a battery temperature model indicating the battery temperature from heat transferred to the battery, a battery voltage-charge model indicating a relationship of an open circuit voltage of the battery and a state of charge of the battery, and a power consumption model indicating a relationship of power consumption of the heating system and heat generated by the heating system.

This provides the advantage that the power distribution can be accurately determined due to the use of these different battery models, thereby achieving an optimal charging of the battery.

According to a second aspect, the invention relates to a vehicle charge control system. The vehicle charge control system includes: an in-vehicle charger for converting alternating current (alternating current, AC) power provided at an AC input to Direct Current (DC) charging power for charging a battery of the vehicle; a heating system including a heating element that heats the battery of the vehicle and a heat controller for controlling heating power of the heating element that heats the battery; a vehicle control unit for vehicle power management according to any preceding claim.

The vehicle charge control system provides an efficient solution for charging a battery of an electric vehicle at low temperatures. The globally optimal power allocation according to the optimal control solution can be easily detected. The application-independent charging may be performed according to an optimal charging strategy independent of the maximum power of the OBC, battery chemistry or thermal system type.

In an exemplary embodiment of the vehicle charging control system, the vehicle control unit is configured to send a first signaling message to the on-board charger, wherein the first signaling message indicates a first portion for charging the battery; the vehicle control unit is configured to send a second signaling message to the thermal controller, wherein the second signaling message indicates a second portion for heating the battery.

This provides the advantage that both units (i.e. the on-board charger and the thermal controller) learn the respective allocated portions of charging power and can apply the respective power allocation.

In an exemplary embodiment of the vehicle charge control system, the vehicle control unit is configured to receive a third signaling message from the battery management system, the third signaling message indicating the battery temperature.

This provides the advantage that the VCU learns the battery temperature from the BMS and can apply this actual battery temperature to determine an optimal power allocation depending on the actual battery temperature.

In an exemplary embodiment of the vehicle charge control system, the vehicle control unit is configured to: transmitting the current vehicle state to network equipment of the cloud network; receiving information about power allocation of the current vehicle state from the network device of the cloud network, wherein the current vehicle state comprises at least one of: the battery temperature, the state of charge of the battery, the maximum power provided by the on-board charger, and the departure time.

This provides the advantage that the network device can solve the optimality problem. This saves processing power of the VCU. VCU may be designed for low processing power.

According to a third aspect, the invention relates to a method for vehicle power management. The method comprises the following steps: receiving battery temperature data, the battery temperature data being indicative of a battery temperature of a battery of the vehicle; determining a power distribution for distributing charging power provided by a charging system based on a comparison of the battery temperature and a temperature threshold, wherein the power distribution indicates dividing the charging power into a first portion for charging the battery by the charging system and a second portion for heating the battery by a heating system; information about the first portion of the charging power is sent to the charging system and information about the second portion of the charging power is sent to the heating system.

This approach provides the same advantage as the VCU described above, namely an efficient solution for charging the battery of an electric vehicle at low temperatures. The method can easily detect globally optimal power allocation according to an optimal control solution. With this approach, application independent charging can be performed according to an optimal charging strategy independent of the maximum power of the OBC, battery chemistry or thermal system type.

According to a fourth aspect, the invention relates to a network device of a cloud network, wherein the network device is configured to: receiving a current vehicle state from a vehicle control unit of a vehicle, the current vehicle state including battery temperature data indicative of a battery temperature of a battery of the vehicle; a memory segment storing one or more predefined values is sent to the vehicle control unit in dependence of a comparison of the battery temperature with a temperature threshold, wherein the memory segment is for storing a power allocation allocating charging power provided by a charging system, wherein the power allocation indicates a division of the charging power into a first part for charging the battery by the charging system and a second part for heating the battery by a heating system.

The network device provides an efficient solution for charging the battery of an electric vehicle at low temperatures. Another advantage is that the process of optimal power allocation may be performed by the network device, which may save processing power of the VCU, thereby saving battery and extending battery life.

The term "based on a comparison of the battery temperature to a temperature threshold" means that the battery exhibits derating behavior, limiting the maximum charging current.

The derating curve is an input to the optimization task as described above in connection with the first aspect.

In an exemplary embodiment of the network device, the vehicle state further comprises at least one of the following information: the state of charge of the battery, the maximum power provided by the charging system for charging the battery, the departure time of the vehicle.

This provides the advantage that the network device can accurately determine the optimal power allocation when the data of these states of charge, maximum power and departure time can be taken into account.

In an exemplary embodiment of the network device, the power allocation is based on a charging strategy indicating the power allocation as a function of the state of charge of the battery and the battery temperature during a charging time.

This provides the advantage that the network device can determine the charging strategy offline and that the scheme of the optimal charging strategy for different initial conditions can be efficiently provided to the VCU.

In an exemplary embodiment of the network device, the network device is configured to: determining an estimated vehicle state of the vehicle by applying the charging strategy to an initial vehicle state received from the vehicle control unit; determining a deviation between the estimated vehicle state and a current vehicle state received from the vehicle control unit; if the deviation exceeds a threshold, the charging strategy is updated.

This provides the advantage that the charging strategy can be updated from time to time if the vehicle state changes.

The current vehicle state and the estimated vehicle state may be compared at regular time intervals, for example, every 15 minutes. After which a new vehicle state is received. For example, after 15 minutes, the initial vehicle state is replaced with the current vehicle state. 15 minutes is just one example. This may be calibrated by a system developer or system design.

According to a fifth aspect, the invention relates to a computer program product. The computer program product comprises computer executable code or computer executable instructions. The computer-executable code or computer-executable instructions, when executed, cause at least one computer to perform the method according to the third aspect described above.

The computer program product may run on a vehicle control unit as described above in connection with the first aspect, or on any controller or processor performing power management.

According to a sixth aspect, the invention relates to a computer readable medium. The computer readable medium stores instructions which, when executed by a computer, cause the computer to perform the method according to the third aspect described above. Such computer readable media may be non-transitory readable storage media. The instructions stored on the computer readable medium may be executed by a controller or processor, for example by a vehicle control unit according to the first aspect.

Drawings

Other embodiments of the invention will be described in conjunction with the following drawings, in which:

fig. 1 shows a block diagram of a vehicle charge control system 100 according to the present invention;

fig. 2 shows a schematic diagram of an optimal power allocation 200 according to the present invention;

fig. 3 shows a schematic diagram of two examples 301 and 302 of a power derating characteristic 300 of an HV battery with respect to temperature;

FIG. 4 shows a schematic diagram of an exemplary algorithm 400 for solving an optimal control problem according to the present invention;

FIG. 5 shows a schematic diagram of a method 500 for solving an optimal control problem according to the present invention;

FIG. 6 illustrates a schematic diagram of a method 600 for vehicle power management in accordance with the present invention;

fig. 7 shows a circuit diagram of an electrical model 700 for obtaining a charging strategy for optimal distribution of charging power according to the invention.

Detailed Description

In the following detailed description, reference is made to the accompanying drawings which form a part hereof, and in which is shown by way of illustration specific aspects of the invention which may be practiced. It is to be understood that other aspects may be utilized and structural or logical changes may be made without departing from the scope of the present invention. The following detailed description is, therefore, not to be taken in a limiting sense, and the scope of the present invention is defined by the appended claims.

It should be understood that the comments pertaining to the described methods are also applicable to the corresponding devices or systems used to perform the methods and vice versa. For example, if a specific method step is described, the corresponding apparatus may comprise means for performing the described method step, even if such means are not elaborated or illustrated in the figures. Furthermore, it should be understood that features of the various exemplary aspects described herein may be combined with each other, unless explicitly stated otherwise.

Fig. 1 shows a block diagram of a vehicle charge control system 100 according to the present invention.

The vehicle charge control system 100 includes the following modules:

1) An in-vehicle Charger (On-Board Charger, OBC) 135: OBC 135 represents an AC/DC converter with maximum output DC power. The OBC 135 is connected to the HV battery 120 over a DC link and enables HV charging. At the other end, the OBC 135 is connected to an electric vehicle supply equipment (electric vehicle supply equipment, EVSE) 138. The electric vehicle supply equipment 138 is an AC charging station with a single-phase or three-phase maximum output AC power, typically placed outside the vehicle.

2) Thermal system/heating element 141: in the present invention, the application of the thermal system 141 is limited to the heating function of heating the battery 120. The heating element 141 may have a continuous (e.g., heat pump) or discrete nature (PTC heater) power consumption and may be coupled with auxiliary consumers that facilitate heat transfer to the battery 120. In the present invention, the heating element 141 is considered at a system level, in which a relationship between input electric power and output heat is modeled.

3) The vehicle control unit 110: VCU 110 represents a domain controller for HV power management. The VCU 110 allocates the power consumption limits of the thermal system 141 and sets the current demand of the on-board charger 135.

4) HV battery 120 with minimum and maximum operating voltages, curves of SoC versus OCV at different temperatures. The HV battery 120 represents a battery 120 for driving an electric vehicle.

5) Tbox 163: tbox or T-Box represents a device for downloading and uploading sampled data to the cloud network 160. Cloud network 160 is located outside the vehicle.

6) Thermal control unit 142: the thermal control unit 142 represents a controller for adjusting thermal power consumption.

7) User interface 150: user interface 150 represents an interface for setting the expected departure time.

The scheme depicted in fig. 1 is based on a mathematical model of the presence of a priori knowledge or empirical data or the following information: battery self-heating models depending on different charging currents/powers; a battery temperature profile based on heat transferred to the battery; a plot of battery OCV versus SOC (open circuit voltage versus state of charge); the power consumption of the thermal system 141 is related to the amount of heat generated by the thermal system 141.

The vehicle charge control system 100 is described in more detail below.

The vehicle charge control system 100 includes an on-vehicle charger 135. The on-board charger 135 is configured to convert alternating current (alternating current, AC) power 136 provided by an AC input 136a into Direct Current (DC) charging power 134 for charging the battery 120 of the vehicle. The AC input 136a may be connected to an electric vehicle supply equipment (electric vehicle supply equipment, EVSE), i.e. a power supply unit external to the vehicle. Both the EVSE and the on-board charger 135 form a charging system 130 for charging the battery 120. In another embodiment, the EVSE may be a power supply unit inside the vehicle, i.e., inside the vehicle charge control system 100.

The vehicle charge control system 100 includes a heating system 140. The heating system 140 includes a heating element 141 that heats the battery 120 of the vehicle and a thermal controller 142 for controlling heating power of the heating element that heats 143 the battery 120. The heating system 140 may be placed inside the vehicle, i.e., inside the vehicle charge control system 100. In another embodiment, the heating system 140 may be placed outside the vehicle as an external heating system, which may be placed near the battery, for example, manually.

The vehicle charge control system 100 includes a vehicle control unit 110 for vehicle power management.

The vehicle control unit 110 is configured to receive battery temperature data indicative of a battery temperature 111 of the vehicle battery 120. Battery temperature data may be received from the battery management system (battery management system, BMS) 121.

The vehicle control unit 110 is configured to determine a power distribution 133 based on a comparison of the battery temperature 111 and a temperature threshold, the power distribution 133 being configured to distribute charging power 134 provided by the charging system 130. The temperature threshold may refer to a temperature below which the temperature is designated as a low temperature at which power allocation may be performed.

The power distribution 133 indicates that the charging power 134 is divided into a first portion 131 for charging the battery 120 by the charging system 130 and a second portion 132 for heating the battery 120 by the heating system 140.

The vehicle control unit 110 is configured to send information 112 about a first portion 131 of the charging power 134 to the charging system 130 and to send information 113 about a second portion 132 of the charging power 134 to the heating system 140.

This information 112, 113 may be sent directly to the charging system 130 and the heating system 140, or indirectly through other electronic or electrical components. For example, the information 112, 113 may be stored in a memory or cloud, and the charging system 130 and the heating system 140 may access the memory or cloud to receive the information 112, 113.

Battery temperature data including battery temperature may be received from the battery management system (Battery Management System, BMS) 121 shown in fig. 1. The battery management system 121 is connected to all of the battery cells of the battery pack (i.e., the battery 120) and receives voltage and temperature information monitored by the sensors from each module. The BMS121 also has a current sensor for monitoring the current in the battery pack. The BMS121 may transmit the minimum and maximum battery temperatures, as well as the SoC, soH, etc., to the VCU 110.

The temperature threshold means that full-power charging cannot be performed below this temperature. For example 10 ℃, but the temperature threshold is highly dependent on the cell manufacturer and the cell topology inside the battery (e.g., how many cells are connected in series or parallel). An alternative temperature threshold may be 0 ℃ to 20 ℃, for example in steps of 1 ℃.

The power allocation 133 may include a power allocation factor 201, such as a factor λ shown in fig. 2. The power split factor 201 indicates a first portion of the charging power 134 for charging the battery 120 and a second portion of the charging power 134 for heating the battery 120.

The power allocation 133 may be based on a charging policy. The charging strategy indicates a power distribution 133 based on the state of charge of the battery 120 and the battery temperature 111 during the charging time.

The goal of the charging strategy is to find the optimal power allocation to perform the maximum charging of the battery. The optimal charging strategy refers to following the power allocation obtained from solving the optimization problem. The VCU 110 requests (via the thermal control unit 142) that the heating system 140 operate at lambda times the power of the charger at each time step/interval. Lambda (lambda) is an optimized solution, varying according to the time step used in solving the problem (e.g., every 30 seconds, 1 minute, etc.).

The power allocation 133 may be based on, for example, at least one of the following: the thermal model of the battery 120, the derating models 301 and 302 of the battery 120 as shown in fig. 3, the power consumption model of the heating system 140, the relationship between the heat generated by the heating system 140 and the corresponding power consumption, and the electrical model of the battery 120. A graphical representation of these different models is shown and described in connection with fig. 7.

The thermal model of the battery may include the following: a) The battery based on the charging current generates heat, b) the battery temperature based on the received heating power changes.

The derating model of the battery describes the maximum charge current as a function of temperature, for example, according to derating curves 301 and 302 shown in fig. 3.

The power consumption model of the heating system may be determined under different conditions.

The electrical model of the battery describes the relationship between SoC current and voltage.

The electrical model of the battery determines the SoC and voltage.

The thermal model of the battery determines the temperature change of the battery.

The model of the heater determines the power consumption and the amount of heat generated. The heater has no universal model because the heater is highly dependent on the chosen thermal system.

The derate model determines the maximum current that the battery can receive.

All of these models interact for the following reasons, as described below in connection with fig. 7:

the voltage and SoC vary with the charge current. The temperature of the battery varies with the heat and internal resistance generated by the heating element. If the temperature of the battery changes, the maximum current that the battery can receive varies according to the derating curve. The amount of heat generated by the heating element depends on the amount of power distributed by the VCU. The amount of power allocated to the heating element is an optimized solution or implicitly the power allocation between the heater and the battery charge.

The charging strategy may be used to obtain a maximum state of charge of battery 120 during charging time interval 151.

The maximum state of charge at the end of the charging session may be obtained by defining a cost function for the optimizer, for example the following cost function. C=100% -SoC (tf). SoC (tf) is the SoC at the end of the optimization period, and corresponds to the SoC at the end of the charging session. The task of the optimizer is to minimize this function while finding the optimal power allocation λ. After solving this problem, one can find the power allocation that maximizes the SoC at tf. The cost function is defined as the difference between 100% SoC and final SoC, so maximizing the final SoC results in minimizing the cost function.

The vehicle control unit 110 may include a user interface 150. The user interface 150 is for receiving a charging time interval from a user input as a time constraint 151. For example, the user may set the desired departure time through the user interface 150. The charging time interval may be a time difference between the current time and an expected departure time set by the user.

The vehicle control unit 110 may be configured to receive the power allocation 133 from a memory segment (e.g., the lookup table 520 shown in fig. 5) storing one or more predefined values. The memory segment is used to store power allocations 133 for successive charge times.

The vehicle control unit 110 may be configured to download the memory segment from a network device of the cloud network 160 as described below.

The cloud network 160 is an external network located outside the vehicle charge control system 100. A telematics Box (Tbox or T-Box) 163, located in the vehicle or inside the vehicle charge control system 100, respectively, is used to communicate with network devices of the cloud network 160 to send and/or receive data. The Tbox 163 is a control center for telematics, and is responsible for a remote connection control function of the vehicle. The Tbox 163 can communicate with the cloud network 160 using the telematics communication standard C-V2X as an example.

The vehicle control unit 110 may be configured to send the current vehicle state 161 to a network device of the cloud network 160, for example, via a Tbox 163, and to receive information about the power allocation 133 of the current vehicle state from the network device of the cloud network 160, for example, via the Tbox 163. The current vehicle state 161 may include at least one of: battery temperature, state of charge of battery 120, maximum power provided by on-board charger 135, departure time.

The state of charge of a battery, also known as "state of charge" (SoC), is defined as the available capacity Q (t) and the maximum possible charge that can be stored in the battery (i.e., the nominal capacity Q _n ) Is a ratio of (2). The SOC of the fully charged battery is 1 or 100%, and the SOC of the fully discharged battery is 0 or 0%.

The maximum power provided by the charging system 130 is the highest power that the on-board charger 135 can output to charge the battery 120 and/or the heating system 140. The maximum power is based on the design of the on-board charger 135.

The departure time is the time at which the user is expected or expecting to start his vehicle, i.e. the time difference between the current time and the expected or expected departure time. Different charging systems may have different charging powers, e.g., 3kW, 7kW, 11kW, etc.

The power allocation 133 may be based on: the derating function of the battery 120 based on the battery temperature 111 is shown in fig. 3.

The derating function is a function that gives a relationship between the battery temperature and the maximum charge power or current that the battery can receive. This relationship depends on the cell chemistry and safety margin chosen by the system designer.

The power allocation 133 may be based on: the voltage of the battery 120 based on the state of charge of the battery 120.

The nominal voltage of the battery depends on the state of charge of the battery, and also on the current due to the internal resistance and capacitance of the battery. When the battery is fully charged, the voltage provided by the battery may be higher than an empty battery. There is a relationship between the state of charge of the battery and the voltage provided by the battery, which can be described by a specific function.

The power allocation 133 may be based on at least one of the following information: a battery self-heating model indicating the battery temperature 111 according to a charging current or power, a battery temperature model indicating the battery temperature 111 according to an amount of heat transferred to the battery 120, a battery voltage-charge model indicating a relationship between an open circuit voltage of the battery 120 and a state of charge of the battery 120, and a power consumption model indicating a relationship between power consumption of the heating system 140 and an amount of heat 143 generated by the heating system 140.

The vehicle control unit 110 may be configured to send a first signaling message 112 to the on-board charger 135. The first signaling message 112 may indicate a first portion 131 for charging the battery 120.

The vehicle control unit 110 may be configured to send a second signaling message 113 to the thermal controller 142. The second signaling message 113 may indicate a second portion 132 for heating the battery 120.

The vehicle control unit 110 may be configured to receive a third signaling message from the battery management system 121. The third signaling message may indicate the battery temperature 111.

The network device of cloud network 160 may be, for example, a computer server. The network device may be used to receive a current vehicle state 161 from the vehicle control unit 110 of the vehicle. The current vehicle state 161 may include: battery temperature data indicating a battery temperature 111 of the battery 120.

The network device may be configured to send a memory segment (e.g., lookup table 520 shown in fig. 5) storing one or more predefined values to the vehicle control unit based on the comparison of the battery temperature 111 to the temperature threshold.

A memory segment, such as a lookup table 520, may be used to store the power allocation 133 that allocates the charging power 134 provided by the charging system 130.

The term "based on the comparison of the battery temperature 111 with the temperature threshold" means that the battery exhibits derating behavior, limiting the maximum charging current, as shown in fig. 3. The derate curve is an input to the optimization task defined above, described in more detail below in connection with FIG. 7.

The vehicle state 161 may also include at least one of the following information: the state of charge of the battery 120, the maximum power provided by the charging system 130 for charging the battery 120, the departure time of the vehicle.

The power allocation 133 may be based on a charging policy. The charging strategy indicates power distribution according to the charging state of the battery and the temperature of the battery in the charging time.

The network device is configured to: determining an estimated vehicle state of the vehicle by applying the charging strategy to the initial vehicle state 161 received from the vehicle control unit 110; determining a deviation between the estimated vehicle state and the current vehicle state 161 received from the vehicle control unit 110; if the deviation exceeds a threshold, the charging strategy is updated.

The current vehicle state and the estimated vehicle state may be compared at regular time intervals, for example, every 15 minutes as shown in fig. 5. After which a new vehicle state may be received. For example, after 15 minutes, the initial vehicle state may be replaced with the current vehicle state. 15 minutes is just one example. This may be calibrated by a system developer or system design.

Fig. 2 shows a schematic diagram of an optimal power allocation 200 according to the present invention.

An external charger, such as the EVSE 138 of the charging system 130 shown in fig. 1, provides charging power 134. The charging power 134 is distributed by an optimal power divider corresponding to the power distribution 133 described above in connection with fig. 1. The charging power 134 is divided into a first portion 131 for charging the battery and a second portion 132 for heating the battery 120 by an external heater (e.g., heating element 141 of heating system 140 shown in fig. 1). The term "external heater" means that the heater 141 is placed outside the battery 120.

The first portion 131 of the charging power 134 may be P _batt ＝(1-λ)P _charger I.e., (1-lambda) times the charging power 134. The second portion 132 of the charging power 134 may be P _heat ＝λP _charger I.e. lambda times the charging power 134. Due to the power conversion from electric power to thermal power, the efficient thermal power for heating the battery may be alpha P _heat Wherein α is between 0 and 1.

The optimal allocation problem can be reduced to an optimal control problem. The objective of the optimal control problem is: an optimal power allocation lambda of the charging power provided by the OBC135 is found between the power 131 provided to the battery 120 for charging and the power 132 consumed by the thermal system 141 to provide heat to the battery 120, thereby providing heat to the battery 120 as described in fig. 2.

The mathematical formula for the optimal control problem can be summarized as follows:

I _batt，lim (x ₂ )→Derating function based on temperature

V _batt (x ₁ )→Battery voltage based on SoC

Cost function J＝100％-x _1，f

(achieving highest SoC at the end of charging)

Wherein SoC represents the state of charge of the HV battery; t represents the average temperature of the HV battery, or the lowest cell temperature of the battery, the derivative of SoC being the time derivative of SoC; alpha corresponds to a variable factor of heat transfer from the heating element to the HV battery; beta corresponds to the variable factor of battery self-heating during charging, V _batt Representing SoC-based battery voltage; i _{bat_max} A temperature-based HV battery current derating curve is represented.

The cost function J models the difference between the full battery SoC (100%) and the final SoC at the end of the charging session.

As an algorithm for solving the optimal control problem, dynamic planning may be used, which allows searching for global optima using the variable control input λ. Algorithmic discretization may be required to reflect the computational steps and discrete nature of the communication signals within the system. The flow chart shown in fig. 4 shows the steps that need to be taken to apply this algorithm to the problem being handled.

Fig. 3 shows a schematic diagram of two examples 301 and 302 of the power derating characteristic 300 of the HV battery with respect to temperature.

The derating model of the battery 120 describes the maximum charge current based on the battery temperature. The first curve 301 represents a first derating model of the first derating type (I). The second curve 302 represents a second derating model of a second derating type (II). The first curve 301 is an example having a stepped profile, and the second curve 302 is an example having a continuous profile (e.g., a monotonically increasing profile).

Fig. 3 shows two temperature thresholds 303, 304, a first temperature threshold 303 representing the lowest temperature at which charging is allowed, and a second temperature threshold 304 representing the temperature at which charging is allowed without derating.

The derate model determines the maximum current that the battery can receive. If the temperature of the battery changes, the maximum current that the battery can receive varies according to the derating curve.

Derating curves 301 and 302 shown in fig. 3 illustrate two examples of derating functions. The derating function is a function that gives a relationship between the battery temperature and the maximum charge power or current that the battery can receive. This relationship depends on the cell chemistry and safety margin chosen by the system designer.

Fig. 4 shows a schematic diagram of an exemplary algorithm 400 for solving an optimal control problem according to the present invention.

The algorithm 400 starts at a first step block 401 of data preparation comprising the following functions: the relationship between SoC and OCV and HV battery temperature; relationship between HV battery temperature and heating power; alpha-curves; beta-curves; relationship between thermal system power consumption and heat generation.

Then, in a second step block 402, an initialization is performed, i.e. an initialization of the maximum power of the OBC and time constraints.

In a next third step block 403, a processing cost matrix is generated, i.e. for each control input λ, the transition cost from state k to state k+1 is calculated.

In a next fourth step block 404, a reverse calculation is performed, i.e. the optimal control λ from state k+1 to state k is selected such that the cost from N to k is optimal.

In a next fifth step block 405, a forward calculation is performed, i.e. the initial state vector x is selected and the optimal lambda is found from the reverse calculation.

In a next sixth step block 406, the optimal strategy is stored in a look-up table.

In a next seventh step block 407, different constraints are selected in combination with the OBC maximum power and time constraints.

Upon processing all initialization conditions, the algorithm 400 ends at step 408; otherwise, the algorithm jumps back to the second step block 402 to perform a new initialization of the OBC maximum power and time constraints.

The algorithm 400 provides the following advantages: optimally controlling the global optimality of the solution; applicability independent of OBC maximum power, battery chemistry, and thermal system type; scalability to multi-objective optimization. For example, optimizing the final temperature by SoC boundary conditions; the cost function is optimized by different weighting factors of the final SoC and the final temperature.

Fig. 5 shows a schematic diagram of a method 500 for solving an optimal control problem according to the present invention. The method may be represented by the functional step blocks shown in fig. 5, as described below.

Initially, in a first step block 501, the user selects "remote charge" or any similar function, and inputs "departure time" via the user interface 150 (e.g., a smartphone or any other control device). The user interface 150 corresponds to the user interface 150 shown in fig. 1. The departure time specifies an expected departure time for starting the vehicle battery.

In a second step block 502, the user selects "optimize charging feature" or any similar function through the user interface 150.

In a third step block 503, the vehicle wakes up and begins communicating with the vehicle control unit 110 the current vehicle state, such as SoC, battery temperature, OBC maximum power, EVSE maximum power, etc.

In a fourth step block 504, if the temperature is below the temperature threshold, the method 500 checks if the initial conditions require an optimized charging strategy. This means checking whether the battery is cold and cannot be charged at the maximum charge rate.

If this is not the case, then in a next step block 507, the VCU 110 applies a default charging policy. Then, in step block 509, charging and/or heating is handled according to a default policy.

In a next step block 511, the method 500 checks if the completion of the charging time is reached, e.g. the end time of the charging process, which may be specified by a default policy. If the completed charge time has not been reached, the method 500 jumps to step 509 to continue charging and/or heating according to a default strategy. If the complete charge time is reached, then the charge is completed in step 513.

If it is detected in step 504 that the temperature is below the temperature threshold, the method proceeds to a next step 505, where it is checked whether the initial conditions have been stored as a look-up table in the cloud network 160.

If this is not the case, in a next step block 506, AI (artificial intelligence) based regression is performed to obtain the optimal strategy according to the initial conditions.

After having processed step block 504 or after having processed step block 504 and step block 506, method 500 continues with step block 508, wherein VCU 110 downloads the optimal policy from cloud network 160. The optimal policy may be received from cloud network 160 (i.e., a network device in cloud network 160) by requesting or accessing a lookup table 520 or memory segment storing the optimal policy as described above in connection with fig. 1. The optimal strategy may be stored in the form of a table with time values (e.g., t1, t2, t3, t … … t_f) and corresponding power allocation values λ. Exemplary time intervals are 1 minute, 2 minutes, 5 minutes, 10 minutes, 15 minutes, 30 minutes, or any other time value.

After downloading the optimal strategy in step block 508, in a next step block 510, the charging and/or heating process is started according to the optimal strategy.

In a next step block 512, the method 500 checks if the complete charge time is reached. If the complete charge time is reached, then the charge is completed in step 513. If the complete charge time has not been reached, the method 500 continues to block 514 where it is checked whether a comparison time has been reached, e.g., every 15 minutes.

If the comparison time is not reached, the method jumps back to step 510 and continues to perform charging and/or heating according to the optimal strategy. If the comparison time is reached, the method continues to step 515 where it is checked whether a significant difference between the current vehicle state and the estimated vehicle state is detected in the cloud. A significant difference is a difference that exceeds a predetermined threshold with respect to one or more vehicle conditions.

If no significant differences are detected, the method 500 continues to step 510 where charging and/or heating is performed according to an optimal strategy. If a significant difference is detected, the method 500 jumps back to step 504, where in step 504 the method 500 checks if the initial conditions require an optimized charging strategy.

Referring to fig. 5, the basic concepts described in the present invention can be summarized by the following items:

1) The optimal charging problem at low temperatures is solved offline, for example, by network devices in the cloud network 160.

2) Solutions for different initial conditions (start SoC, start temperature) and different constraints (OBC maximum power, departure time) are stored in the cloud network 160 in the form of a time series of lambda values 520.

3) The cloud network 160 has computing power for performing a regression operation (in step 506) without storing the current state of the vehicle. For example, the optimal strategy for an initial temperature of-30 ℃ and an initial SoC of 50%, an initial temperature of-35 ℃ and an initial SoC of 50% is stored. The current vehicle state corresponds to an initial temperature of-33 ℃ and an initial SoC of 50%. The optimal solutions for data points-33 ℃ and 50% SoC can then be regressed.

4) The EV vehicle owner may select an option to remotely optimize the low temperature charging, for example, through an App on the mobile device, and may set the expected departure time through the user interface 150.

5) VCU 110 transmits the current vehicle state, such as SoC, battery temperature, OBC maximum power, departure time, etc., to cloud network 160.

6) Cloud network 160 or VCU 110 evaluates whether the temperature condition requires deployment of an optimized charging strategy (in step block 504).

7) If so, the cloud network 160 evaluates whether to store optimal policies for vehicle conditions; if not, approximation is performed by regression from the data points stored in the cloud network 160.

8) The cloud network 160 downloads the policies to the VCU 110 in a time-stamp format with a corresponding control input λ.

9) VCU 110 takes the downloaded policies and deploys the policies on the real system.

10 Cloud network 160 compares the actual system behavior to the estimated system behavior every 15 minutes (or any other predetermined time interval). In the event of an inconsistency, cloud network 160 looks up the optimal policy corresponding to the current vehicle state and updates the policy sent to VCU 110.

11 If the current vehicle state does not require deployment of an optimized charging strategy, a default strategy is used, e.g., charging with maximum battery charging current.

12 If the charge exit condition is satisfied, the charging session ends. For example, reaching the final SoC, reaching the final time, or the charging system failing.

Fig. 6 shows a schematic diagram of a method 600 for vehicle power management according to the present invention.

The method 600 includes receiving 601 battery temperature data. The battery temperature data is indicative of the battery temperature of the vehicle battery, as described above in connection with fig. 1.

The method 600 includes: based on a comparison of the battery temperature and the temperature threshold, a power allocation for allocating charging power provided by the charging system is determined 602, wherein the power allocation indicates dividing the charging power into a first portion for charging the battery by the charging system and a second portion for heating the battery by the heating system, as described above in connection with fig. 1.

The method 600 includes: information about a first portion of the charging power is sent 603 to the charging system and information about a second portion of the charging power is sent 603 to the heating system, as described above in connection with fig. 1.

Fig. 7 shows a circuit diagram of an electrical model for obtaining a charging strategy for optimal distribution of charging power according to the invention.

The electrical model is represented by circuit 700. The circuit 700 includes: first resistor R ₀ Wherein the first resistor R ₀ And a second resistor R ₁ And capacitor C ₁ Is connected in series in parallel. First resistor R ₀ Is connected to a voltage source V ₀ (s[k]). The current through circuit 700 is referred to as i k]The voltage across circuit 700 is referred to as v k]。

To solve the optimization problem, and thus find the optimal charging strategy described above in connection with fig. 2, the following equation needs to be solved for each time step:

a) Three-state dynamic programming (dynamic programming, DP) with current i [ k ] as control (nonlinear system):

b) And (3) an electrical model:

c) Thermal model:

d) Derating model:

i _max ＝f(θ)and i[k]<i _max [θ[k]]

e) Cost function:

j=100% -s [ Nf ], where Nf is the optimal period length corresponding to the final time.

The algorithm may then minimize the cost function and determine the optimal current i k.

While a particular feature or aspect of the invention may have been disclosed with respect to only one of several implementations, such feature or aspect may be combined with one or more other features or aspects of the other implementations as may be desired and advantageous for any given or particular application. Furthermore, to the extent that the terms "includes," has, "" having, "or other variants thereof are used in either the detailed description or the claims, such terms are intended to be inclusive in a manner similar to the term" comprising. Also, the terms "exemplary," "such as," and "for example," are merely meant as examples, rather than as being best or optimal. The terms "coupled" and "connected," along with their derivatives, may be used. It should be understood that these terms may be used to indicate that two elements co-operate or interact with each other regardless of whether they are in direct physical or electrical contact or they are not in direct contact with each other.

Although specific aspects have been illustrated and described herein, it will be appreciated by those of ordinary skill in the art that a variety of alternate and/or equivalent implementations may be substituted for the specific aspects shown and described without departing from the scope of the present invention. This application is intended to cover any adaptations or variations of the specific aspects discussed herein.

Although elements in the following claims are recited in a particular order with corresponding labeling, unless the claim recitations otherwise imply a particular order for implementing some or all of those elements, those elements are not necessarily limited to being implemented in that particular order.

Many alternatives, modifications, and variations will be apparent to those skilled in the art in light of the above teachings. Of course, those skilled in the art will readily recognize that there are numerous other applications of the present invention in addition to those described herein. While the invention has been described with reference to one or more particular embodiments, those skilled in the art will recognize that many changes may be made thereto without departing from the scope of the present invention. It is, therefore, to be understood that within the scope of the appended claims and equivalents thereof, the invention may be practiced otherwise than as specifically described herein.

Claims

1. A vehicle control unit (110) for vehicle power management, characterized in that the vehicle control unit (110) is configured to:

receiving battery temperature data indicative of a battery temperature (111) of a battery (120) of the vehicle;

determining a power distribution (133) based on a comparison of the battery temperature (111) and a temperature threshold, the power distribution (133) being for distributing charging power (134) provided by a charging system (130),

wherein the power distribution (133) indicates a division of the charging power (134) into a first portion (131) for charging the battery (120) by the charging system (130) and a second portion (132) for heating the battery (120) by a heating system (140);

-transmitting information (112) about the first portion (131) of the charging power (134) to the charging system (130), and-transmitting information (113) about the second portion (132) of the charging power (134) to the heating system (140).

2. The vehicle control unit (110) according to claim 1, wherein,

the power distribution (133) comprises a power distribution factor (201), the power distribution factor (201) being indicative of a first portion of the charging power (134) for charging the battery (120) and a second portion of the charging power (134) for heating the battery (120).

3. The vehicle control unit (110) according to claim 1 or 2, characterized in that,

the power distribution (133) is based on a charging strategy that indicates the power distribution (133) as a function of a state of charge of the battery (120) and the battery temperature (111) over a charging time.

4. A vehicle control unit (110) according to claim 3, characterized in that the power distribution (133) is based on at least one of:

a thermal model of the battery (120),

derating models (301 and 302) of the battery (120),

a power consumption model of the heating system (140),

the relation between the heat generated by the heating system (140) and the corresponding power consumption,

an electrical model of the battery (120).

5. The vehicle control unit (110) according to claim 3 or 4, characterized in that,

the charging strategy is used to obtain a maximum state of charge of the battery (120) within a charging time interval (151).

6. The vehicle control unit (110) according to any of the preceding claims, wherein,

the vehicle control unit (110) is configured to receive the power allocation (133) from a memory segment storing one or more predefined values, wherein the memory segment is configured to store the power allocation (133) for successive charging times.

7. The vehicle control unit (110) according to claim 6, wherein,

the vehicle control unit (110) is configured to download the memory segment from a network device of a cloud network (160).

8. The vehicle control unit (110) according to claim 7, wherein the vehicle control unit (110) is configured to:

-sending a current vehicle state (161) to the network device of the cloud network (160);

receiving the memory segment of the current vehicle state (161) from the network device of the cloud network (160),

wherein the current vehicle state (161) comprises at least one of:

the battery temperature (111), the state of charge of the battery (120), the maximum power provided by the charging system (130), the departure time.

9. The vehicle control unit (110) of any of the preceding claims, wherein the power distribution (133) is based on:

-a derating function of the battery (120) based on the battery temperature (111).

10. The vehicle control unit (110) of any of the preceding claims, wherein the power distribution (133) is based on:

-a voltage of the battery (120) based on a state of charge of the battery (120).

11. The vehicle control unit (110) according to any of the preceding claims, wherein the power distribution (133) is based on at least one of the following information:

a battery self-heating model indicating the battery temperature (111) based on the charging current or power,

a battery temperature model indicative of the battery temperature (111) based on heat transferred to the battery (120),

a battery voltage-charge model indicative of a relationship of an open circuit voltage of the battery (120) and a state of charge of the battery (120),

a power consumption model indicative of a relation of power consumption of the heating system (140) to heat (143) generated by the heating system (140).

12. A vehicle charge control system (100), characterized in that the vehicle charge control system (100) includes:

an on-board charger (135), the on-board charger (135) for converting AC power (136) provided by an alternating current (alternating current, AC) input (136 a) to Direct Current (DC) charging power (134) for charging a battery (120) of the vehicle;

-a heating system (140), the heating system (140) comprising a heating element (141) for heating the battery (120) of the vehicle and a thermal controller (142) for controlling the heating power of the heating element for heating (143) the battery (120);

The vehicle control unit (110) for vehicle power management according to any one of the preceding claims.

13. The vehicle charge control system (100) of claim 12, wherein,

-the vehicle control unit (110) is configured to send a first signaling message (112) to the on-board charger (135), wherein the first signaling message (112) indicates a first portion (131) for charging the battery (120);

the vehicle control unit (110) is configured to send a second signaling message (113) to the thermal controller (142), wherein the second signaling message (113) indicates a second portion (132) for heating the battery (120).

14. The vehicle charge control system (100) according to claim 12 or 13, characterized in that,

the vehicle control unit (110) is configured to receive a third signaling message from the battery management system (121), the third signaling message indicating a battery temperature (111).

15. The vehicle charge control system (100) according to any one of claims 12 to 14, wherein the vehicle control unit (110) is configured to:

transmitting the current vehicle state (161) to a network device of a cloud network (160);

receiving information about a power allocation (133) of the current vehicle state from the network device of the cloud network (160),

Wherein the current vehicle state (161) comprises at least one of:

the battery temperature, the state of charge of the battery (120), the maximum power provided by the on-board charger (135), the departure time.

16. A method (600) for vehicle power management, the method (600) comprising:

-receiving (601) battery temperature data indicative of a battery temperature of a battery of the vehicle;

determining (602) a power distribution for distributing charging power provided by a charging system based on a comparison of the battery temperature and a temperature threshold,

wherein the power allocation indication divides the charging power into a first portion for charging the battery by the charging system and a second portion for heating the battery by a heating system;

-transmitting (603) information about the first part of the charging power to the charging system, and-transmitting (603) information about the second part of the charging power to the heating system.

17. A network device of a cloud network (160), the network device being configured to:

receiving a current vehicle state (161) from a vehicle control unit (110) of a vehicle, the current vehicle state (161) comprising battery temperature data indicative of a battery temperature (111) of a battery (120) of the vehicle;

Transmitting a memory segment storing one or more predefined values to the vehicle control unit in dependence of a comparison of the battery temperature (111) with a temperature threshold, wherein the memory segment is adapted to store a power allocation (133) allocating charging power (134) provided by a charging system (130),

wherein the power distribution (133) indicates that the charging power (134) is divided into a first portion (131) for charging the battery by the charging system and a second portion (132) for heating the battery by a heating system.

18. The network device of claim 17, wherein the vehicle status (161) further comprises at least one of the following information:

the state of charge of the battery (120),

the maximum power provided by the charging system (130) for charging the battery (120),

the departure time of the vehicle.

19. The network device of claim 18, wherein the network device,

the power distribution (133) is based on a charging strategy that indicates power distribution according to a state of charge of the battery and the battery temperature over a charging time.

20. The network device of claim 19, wherein the network device is configured to:

Determining an estimated vehicle state of the vehicle by applying the charging strategy to an initial vehicle state (161) received from the vehicle control unit (110);

determining a deviation between the estimated vehicle state and a current vehicle state (161) received from the vehicle control unit (110);

if the deviation exceeds a threshold, the charging strategy is updated.